E mergency Medical Services (EMS) field triage to stroke centers has gained considerable complexity because the demonstration of clinical benefit of endovascular treatment (ET) in recent randomized clinical trials.1 As a result, it has become critical to develop objective prehospital triage criteria that appropriately identify patients who are most likely to benefit from services only available at Comprehensive Stroke Centers (CSCs) and therefore require direct transportation, while also facilitating the proper triage of less complex or lower acuity patients to the nearest stroke center (CSCs, Primary Stroke Centers [PSCs], or Acute Stroke Ready Hospitals [ASRHs]). Proper selection of the destination stroke center will enhance appropriate resource use to meet the needs of individual patients to optimize time to reperfusion and the broader communities by minimizing the time an ambulance is unnecessarily out of service, and will more homogenously distribute patients with stroke to minimize the effects of crowding on a single healthcare system. Although field identification of potential candidates for mechanical thrombectomy is possible using stroke scales designed to recognize large vessel occlusion strokes (LVOS), 2-6 the decision tree is substantially more complex because many of these patients are also candidates for intravenous thrombolysis (IVT), which could often be more promptly provided at a closer location. Therefore, an optimal destination triage algorithm should not only include the probability of LVOS but also include information about Background and Purpose-The Emergency Medical Services field triage to stroke centers has gained considerable complexity with the recent demonstration of clinical benefit of endovascular treatment for acute ischemic stroke. We sought to describe a new smartphone freeware application designed to assist Emergency Medical Services professionals with the field assessment and destination triage of patients with acute ischemic stroke. Methods-Review of the application's platform and its development as well as the different variables, assessments, algorithms, and assumptions involved. Results-The FAST-ED (Field Assessment Stroke Triage for Emergency Destination) application is based on a built-in automated decision-making algorithm that relies on (1) a brief series of questions assessing patient's age, anticoagulant usage, time last known normal, motor weakness, gaze deviation, aphasia, and hemineglect; (2) a database of all regional stroke centers according to their capability to provide endovascular treatment; and (3) Global Positioning System technology with real-time traffic information to compute the patient's eligibility for intravenous tissue-type plasminogen activator or endovascular treatment as well as the distances/transportation times to the different neighboring stroke centers in order to assist Emergency Medical Services professionals with the decision about the most suitable destination for any given patient with acute ischemic stroke. Conclusions-The FAST-ED smar...
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.